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Industrial melt index soft measurement instrument and method based on BP particle swarm optimization

A technology of BP particle swarm and melt index, which is applied in the field of soft measuring instruments, which can solve the problems of difficult parameter selection, low measurement accuracy and low noise sensitivity.

Inactive Publication Date: 2014-03-26
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to overcome the shortcomings of the existing propylene polymerization production process, such as low measurement accuracy, low sensitivity to noise, and difficulty in parameter selection, the present invention provides a BP with online measurement, fast calculation speed, automatic model update, and strong noise resistance. Particle swarm optimized industrial melt index soft measuring instrument and method

Method used

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  • Industrial melt index soft measurement instrument and method based on BP particle swarm optimization
  • Industrial melt index soft measurement instrument and method based on BP particle swarm optimization
  • Industrial melt index soft measurement instrument and method based on BP particle swarm optimization

Examples

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Effect test

Embodiment 1

[0088] refer to figure 1 , figure 2 , an industrial melt index soft measuring instrument optimized by BP particle swarm, including propylene polymerization production process 1, on-site intelligent instrument 2 for measuring easy-to-measure variables, control station 3 for measuring operating variables, and DCS database for storing data 4 And the melt index soft measurement value display instrument 6, the field intelligent instrument 2, the control station 3 are connected with the propylene polymerization production process 1, the field intelligent instrument 2, the control station 3 are connected with the DCS database 4, and the soft measurement instrument is also Including the soft sensor model 5 optimized by the particle swarm optimization BP neural network fuzzy equation, the DCS database 4 is connected to the input end of the industrial melting index soft sensor model 5 optimized by the BP particle swarm optimization, and the industrial melting index soft sensor model 5 ...

Embodiment 2

[0169] refer to figure 1 , figure 2 , a soft-sensing method for propylene polymerization production process based on particle swarm optimization algorithm to optimize BP neural network fuzzy equation model, the specific implementation steps of the soft-sensing method are as follows:

[0170] 1) For the propylene polymerization production process object, according to the process analysis and operation analysis, the operational variables and easily measurable variables are selected as the input of the model, and the operational variables and easily measurable variables are obtained from the DCS database;

[0171] 2) Preprocess the model training samples input from the DCS database, and centralize the training samples, that is, subtract the average value of the samples, and then standardize them so that the mean value is 0 and the variance is 1. This processing is accomplished using the following algorithmic procedure:

[0172] 2.1) Calculate the mean: TX ...

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Abstract

The invention discloses an industrial melt index soft measurement instrument and method based on BP particle swarm optimization. For the industrial melt index soft measurement method, a BP neural network is taken as a local equation of a fuzzy equation system, and then the particle swarm optimization is introduced for further optimizing a whole soft measurement model. According to the invention, an on-site intelligent instrument for measuring easy-to-measure variables, a control station and a DCS (distributed control system) database are connected with one another, a soft measurement value display instrument comprises the industrial melt index soft measurement model based on the BP particle swarm optimization, the DCS database is connected with an input end of the soft measurement model, and an output end of the industrial melt index soft measurement model based on the BP particle swarm optimization is connected with the melt index soft measurement value display instrument. The industrial melt index soft measurement instrument and method have the characteristics of on-line optimization, high calculation speed, automatic updating of the model and high noise immunity.

Description

technical field [0001] The invention relates to a soft measuring instrument and method, in particular to an industrial melt index soft measuring instrument and method optimized by BP particle group. Background technique [0002] Polypropylene is a semi-crystalline thermoplastic polymerized from propylene. It has high impact resistance, strong mechanical properties, and resistance to various organic solvents and acid and alkali corrosion. It is widely used in the industry and is common. One of the most common polymer materials. Melt index (MI) is one of the important quality indicators to determine the grade of the final product in the production of polypropylene, which determines the different uses of the product. Accurate and timely measurement of melt index plays a very important and guiding role in production and scientific research. However, the on-line analysis and measurement of melt index is still difficult to achieve, and the lack of on-line analyzer for melt index...

Claims

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Application Information

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IPC IPC(8): G01N25/04G05B13/04
Inventor 刘兴高张明明李见会
Owner ZHEJIANG UNIV
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